Fuzzy Logic

Non-standard fuzzy sets

Granular computing

Computing with words

Aggregation/fusion

Fuzzy sets and statistics

Uncertainty

Decision-making

General theoretical issues

Generalisation in neural, fuzzy and evolutionary learning

Fuzzy logic and fuzzy set theory

Lattice theory and multi-valued logic

Approximate reasoning

Type-2 fuzzy logic

Rough sets and random sets

Fuzzy mathematics

Fuzzy measure and integral

Possibility theory and imprecise probability

Neural Networks and other machine learning techniques

• Neural computation
• Self-organizing maps
• Recurrent networks
• Multilayer perceptrons
• Recursive deterministic perceptrons
• Evolutionary neural networks
• Neural networks for pattern recognition
• Neural netwoks for prediction and optimization
• Neural networks for principal component analysis
• General regression neural networks
• Neural networks as/and fuzzy systems
• Radial basis functions
• Learning theory
• Reinforcement learning
• Generalization in neural networks

Evolutionary Computation

• • Theoretical foundations of bio-inspired heuristics
  • Exact and approximation runtime analysis
  • Fixed budget computations
  • Black box complexity
  • Self-adaptation
  • Population dynamics
  • Fitness landscape and problem difficulty analysis
  • No Free Lunch Theorems
  • Statistical approaches for understanding the behaviour of bio-inspired heuristics
  • Computational studies of a foundational nature.

Big Data Models, Algorithms and Architectures

• Foundational Models for Big Data

• Algorithms and Programming Techniques for Big Data Processing

• Big Data Analytics and Metrics

• Novel Theoretical Models for Big Data

• New Computational Models for Big Data

• Data and Information Quality for Big Data

• New Data Standards

• Cloud Computing Techniques for Big Data

• Big Data as a Service

• Big Data Open Platforms

• Data Stream Algorithms

• Randomized Algorithms for Matrices and Data

• Algorithmic Techniques for Big Data Analysis

• Models of Computation for Massive Data

• The Modern Algorithmic Toolbox

• Big data storage architecture

• GEOSS clearinghouse

• Distributed and parallel computing

Big Data Management

• Big Data Persistence and Preservation

• Big Data Quality and Provenance Control

• Big Data Storage and Retrieval

• Search and Mining of variety of data including scientific and engineering, social, sensor/IoT/IoE, and multimedia data

• Algorithms and Systems for Big Data Search

• Distributed, and Peer-to-peer Search

• Big Data Search Architectures, Scalability and Efficiency

• Data Acquisition, Integration, Cleaning, and Best Practices

• Visualization Analytics for Big Data

• Computational Modeling and Data Integration

• Large-scale Recommendation Systems and Social Media Systems

• Cloud/Grid/Stream Data Mining- Big Velocity Data

• Link and Graph Mining

• Semantic-based Data Mining and Data Pre-processing

• Mobility and Big Data

• Multimedia and Multi-structured Data- Big Variety Data

Big Data Security, Privacy and Trust

• Big Data System Security and Integrity

• Big Data Information Security

• Privacy Preserving Big Data Analytics

• Usable Security and Privacy for Big Data

• Intrusion Detection for Gigabit Networks

• Anomaly and APT Detection in Very Large Scale Systems

• High Performance Cryptography

• Visualizing Large Scale Security Data

• Threat Detection using Big Data Analytics

• Privacy Threats of Big Data

• Privacy Preserving Big Data Collection/Analytics

• HCI Challenges for Big Data Security & Privacy

• User Studies for any of the above

• Sociological Aspects of Big Data Privacy

• Trust management in IoT and other Big Data Systems

Big Data Search, Mining, and Visualization

• Algorithms and Systems for Big Data Search

• Distributed, and Peer-to-peer Search

• Machine learning based on Big Data

• Visualization Analytics for Big Data

• Social Web Search and Mining

• Web Search

• Algorithms and Systems for Big Data Search

• Distributed, and Peer-to-peer Search

• Big Data Search Architectures, Scalability and Efficiency

• Data Acquisition, Integration, Cleaning, and Best Practices

• Visualization Analytics for Big Data

• Computational Modeling and Data Integration

• Large-scale Recommendation Systems and Social Media Systems

• Cloud/Grid/StreamData Mining- Big Velocity Data

• Link and Graph Mining

• Semantic-based Data Mining and Data Pre-processing

• Mobility and Big Data

• Multimedia and Multi-structured Data-Big Variety Data

• Multifaceted and task-driven search

• Personalized search and ranking

• Data, entity, event, and relationship extraction

• Data integration and data cleaning

• Opinion mining and sentiment analysis

Big Data Applications

• Big Data for Enterprise, Government, and Society
• Case Studies of Big Data Value Creation
• Big Data for Science and Engineering Research
• Complex Big Data Applications in Science, Engineering, Medicine, Healthcare, Finance, Business, Law, Education, Transportation, Retailing, Telecommunication
• Big Data Analytics in Small Business Enterprises (SMEs)
• Big Data Analytics in Government, Public Sector and Society in General
• Real-life Case Studies of Value Creation through Big Data Analytics
• Big Data as a Service
• Big Data Industry Standards
• Experiences with Big Data Project Deployments
• Big Data Analytics in Enterprises
• Big data in eGovernment
• Big data in Mobile apps
• Big data in smart cities
• Big data in Manufacturing
• Big data in security and privacy
• Big data in Ecommerce
• Big data in Biomedicine
• Big data in Regulated Industries
• Big data in clinical and healthcare
• Financial aspects of Big Data Industry
• Current and future scenario of Big Data Market
• Big Data in Travel Industry
• Big Data Trends in Retail
• Big data in Public administration

Big Data Infrastructure

• Cloud/Grid/Stream Computing for Big Data
• High Performance/Parallel Computing Platforms for Big Data
• Autonomic Computing and Cyber-infrastructure, System Architectures, Design and Deployment
• Energy-efficient Computing for Big Data
• Programming Models and Environments for Cluster, Cloud, and Grid Computing to Support Big Data
• Software Techniques andArchitectures in Cloud/Grid/Stream Computing
• Big Data Open Platforms
• New Programming Models for Big Data beyond Hadoop/MapReduce, STORM
• Software Systems to Support Big Data Computing